Ebook: Complete guide to open source big data stack

Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: The Big Data Stack Overview; What Is Big Data?; Limitations of Approach; Why a Stack?; NoSQL Overview; Development Stacks; LAMP Stack; MEAN Stack; SMACK Stack; MARQS Stack; Book Approach; Chapter 2 â#x80;#x93; Cloud Storage; Chapter 3 â#x80;#x93; Release Management â#x80;#x93; Brooklyn; Chapter 4 â#x80;#x93; Resource Management; Chapter 5 â#x80;#x93; Storage; Chapter 6 â#x80;#x93; Processing; Chapter 7 â#x80;#x93; Streaming; Chapter 8 â#x80;#x93; Frameworks; Chapter 9 â#x80;#x93; Data Visualisation; Chapter 10 â#x80;#x93; The Big Data Stack.;See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack--sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You'll Learn: Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing.